{"id":"79c71053-3e2e-4e31-8da1-dd675e9f4895","shortId":"bavqRT","kind":"skill","title":"prompt-library","tagline":"A comprehensive collection of battle-tested prompts inspired by [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) and community best practices.","description":"# 📝 Prompt Library\n\n> A comprehensive collection of battle-tested prompts inspired by [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) and community best practices.\n\n## When to Use This Skill\n\nUse this skill when the user:\n\n- Needs ready-to-use prompt templates\n- Wants role-based prompts (act as X)\n- Asks for prompt examples or inspiration\n- Needs task-specific prompt patterns\n- Wants to improve their prompting\n\n## Prompt Categories\n\n### 🎭 Role-Based Prompts\n\n#### Expert Developer\n\n```\nAct as an expert software developer with 15+ years of experience. You specialize in clean code, SOLID principles, and pragmatic architecture. When reviewing code:\n1. Identify bugs and potential issues\n2. Suggest performance improvements\n3. Recommend better patterns\n4. Explain your reasoning clearly\nAlways prioritize readability and maintainability over cleverness.\n```\n\n#### Code Reviewer\n\n```\nAct as a senior code reviewer. Your role is to:\n1. Check for bugs, edge cases, and error handling\n2. Evaluate code structure and organization\n3. Assess naming conventions and readability\n4. Identify potential security issues\n5. Suggest improvements with specific examples\n\nFormat your review as:\n🔴 Critical Issues (must fix)\n🟡 Suggestions (should consider)\n🟢 Praise (what's done well)\n```\n\n#### Technical Writer\n\n```\nAct as a technical documentation expert. Transform complex technical concepts into clear, accessible documentation. Follow these principles:\n- Use simple language, avoid jargon\n- Include practical examples\n- Structure with clear headings\n- Add code snippets where helpful\n- Consider the reader's experience level\n```\n\n#### System Architect\n\n```\nAct as a senior system architect designing for scale. Consider:\n- Scalability (horizontal and vertical)\n- Reliability (fault tolerance, redundancy)\n- Maintainability (modularity, clear boundaries)\n- Performance (latency, throughput)\n- Cost efficiency\n\nProvide architecture decisions with trade-off analysis.\n```\n\n### 🛠️ Task-Specific Prompts\n\n#### Debug This Code\n\n```\nDebug the following code. Your analysis should include:\n\n1. **Problem Identification**: What exactly is failing?\n2. **Root Cause**: Why is it failing?\n3. **Fix**: Provide corrected code\n4. **Prevention**: How to prevent similar bugs\n\nShow your debugging thought process step by step.\n```\n\n#### Explain Like I'm 5 (ELI5)\n\n```\nExplain [CONCEPT] as if I'm 5 years old. Use:\n- Simple everyday analogies\n- No technical jargon\n- Short sentences\n- Relatable examples from daily life\n- A fun, engaging tone\n```\n\n#### Code Refactoring\n\n```\nRefactor this code following these priorities:\n1. Readability first\n2. Remove duplication (DRY)\n3. Single responsibility per function\n4. Meaningful names\n5. Add comments only where necessary\n\nShow before/after with explanation of changes.\n```\n\n#### Write Tests\n\n```\nWrite comprehensive tests for this code:\n1. Happy path scenarios\n2. Edge cases\n3. Error conditions\n4. Boundary values\n\nUse [FRAMEWORK] testing conventions. Include:\n- Descriptive test names\n- Arrange-Act-Assert pattern\n- Mocking where appropriate\n```\n\n#### API Documentation\n\n```\nGenerate API documentation for this endpoint including:\n- Endpoint URL and method\n- Request parameters (path, query, body)\n- Request/response examples\n- Error codes and meanings\n- Authentication requirements\n- Rate limits if applicable\n\nFormat as OpenAPI/Swagger or Markdown.\n```\n\n### 📊 Analysis Prompts\n\n#### Code Complexity Analysis\n\n```\nAnalyze the complexity of this codebase:\n\n1. **Cyclomatic Complexity**: Identify complex functions\n2. **Coupling**: Find tightly coupled components\n3. **Cohesion**: Assess module cohesion\n4. **Dependencies**: Map critical dependencies\n5. **Technical Debt**: Highlight areas needing refactoring\n\nRate each area and provide actionable recommendations.\n```\n\n#### Performance Analysis\n\n```\nAnalyze this code for performance issues:\n\n1. **Time Complexity**: Big O analysis\n2. **Space Complexity**: Memory usage patterns\n3. **I/O Bottlenecks**: Database, network, disk\n4. **Algorithmic Issues**: Inefficient patterns\n5. **Quick Wins**: Easy optimizations\n\nPrioritize findings by impact.\n```\n\n#### Security Review\n\n```\nPerform a security review of this code:\n\n1. **Input Validation**: Check all inputs\n2. **Authentication/Authorization**: Access control\n3. **Data Protection**: Sensitive data handling\n4. **Injection Vulnerabilities**: SQL, XSS, etc.\n5. **Dependencies**: Known vulnerabilities\n\nClassify issues by severity (Critical/High/Medium/Low).\n```\n\n### 🎨 Creative Prompts\n\n#### Brainstorm Features\n\n```\nBrainstorm features for [PRODUCT]:\n\nFor each feature, provide:\n- Name and one-line description\n- User value proposition\n- Implementation complexity (Low/Med/High)\n- Dependencies on other features\n\nGenerate 10 ideas, then rank top 3 by impact/effort ratio.\n```\n\n#### Name Generator\n\n```\nGenerate names for [PROJECT/FEATURE]:\n\nProvide 10 options in these categories:\n- Descriptive (what it does)\n- Evocative (how it feels)\n- Acronyms (memorable abbreviations)\n- Metaphorical (analogies)\n\nFor each, explain the reasoning and check domain availability patterns.\n```\n\n### 🔄 Transformation Prompts\n\n#### Migrate Code\n\n```\nMigrate this code from [SOURCE] to [TARGET]:\n\n1. Identify equivalent constructs\n2. Handle incompatible features\n3. Preserve functionality exactly\n4. Follow target language idioms\n5. Add necessary dependencies\n\nShow the migration step by step with explanations.\n```\n\n#### Convert Format\n\n```\nConvert this [SOURCE_FORMAT] to [TARGET_FORMAT]:\n\nRequirements:\n- Preserve all data\n- Use idiomatic target format\n- Handle edge cases\n- Validate the output\n- Provide sample verification\n```\n\n## Prompt Engineering Techniques\n\n### Chain of Thought (CoT)\n\n```\nLet's solve this step by step:\n1. First, I'll understand the problem\n2. Then, I'll identify the key components\n3. Next, I'll work through the logic\n4. Finally, I'll verify the solution\n\n[Your question here]\n```\n\n### Few-Shot Learning\n\n```\nHere are some examples of the task:\n\nExample 1:\nInput: [example input 1]\nOutput: [example output 1]\n\nExample 2:\nInput: [example input 2]\nOutput: [example output 2]\n\nNow complete this:\nInput: [actual input]\nOutput:\n```\n\n### Persona Pattern\n\n```\nYou are [PERSONA] with [TRAITS].\nYour communication style is [STYLE].\nYou prioritize [VALUES].\n\nWhen responding:\n- [Behavior 1]\n- [Behavior 2]\n- [Behavior 3]\n```\n\n### Structured Output\n\n```\nRespond in the following JSON format:\n{\n  \"analysis\": \"your analysis here\",\n  \"recommendations\": [\"rec1\", \"rec2\"],\n  \"confidence\": 0.0-1.0,\n  \"caveats\": [\"caveat1\"]\n}\n```\n\n## Prompt Improvement Checklist\n\nWhen crafting prompts, ensure:\n\n- [ ] **Clear objective**: What exactly do you want?\n- [ ] **Context provided**: Background information included?\n- [ ] **Format specified**: How should output be structured?\n- [ ] **Examples given**: Are there reference examples?\n- [ ] **Constraints defined**: Any limitations or requirements?\n- [ ] **Success criteria**: How do you measure good output?\n\n## Resources\n\n- [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts)\n- [prompts.chat](https://prompts.chat)\n- [Learn Prompting](https://learnprompting.org/)\n\n---\n\n> 💡 **Tip**: The best prompts are specific, provide context, and include examples of desired output.\n\n## Limitations\n- Use this skill only when the task clearly matches the scope described above.\n- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.\n- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.","tags":["prompt","library","antigravity","awesome","skills","sickn33","agent-skills","agentic-skills","ai-agent-skills","ai-agents","ai-coding","ai-workflows"],"capabilities":["skill","source-sickn33","skill-prompt-library","topic-agent-skills","topic-agentic-skills","topic-ai-agent-skills","topic-ai-agents","topic-ai-coding","topic-ai-workflows","topic-antigravity","topic-antigravity-skills","topic-claude-code","topic-claude-code-skills","topic-codex-cli","topic-codex-skills"],"categories":["antigravity-awesome-skills"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/sickn33/antigravity-awesome-skills/prompt-library","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"cli":"npx skills add sickn33/antigravity-awesome-skills","source_repo":"https://github.com/sickn33/antigravity-awesome-skills","install_from":"skills.sh"}},"qualityScore":"0.700","qualityRationale":"deterministic score 0.70 from registry signals: · indexed on github topic:agent-skills · 34616 github stars · SKILL.md body (7,602 chars)","verified":false,"liveness":"unknown","lastLivenessCheck":null,"agentReviews":{"count":0,"score_avg":null,"cost_usd_avg":null,"success_rate":null,"latency_p50_ms":null,"narrative_summary":null,"summary_updated_at":null},"enrichmentModel":"deterministic:skill-github:v1","enrichmentVersion":1,"enrichedAt":"2026-04-23T00:51:26.496Z","embedding":null,"createdAt":"2026-04-18T21:42:58.584Z","updatedAt":"2026-04-23T00:51:26.496Z","lastSeenAt":"2026-04-23T00:51:26.496Z","tsv":"'-1.0':868 '/)':931 '/f/awesome-chatgpt-prompts)':20,43,924 '0.0':867 '1':123,161,303,378,413,488,532,573,688,757,802,806,810,846 '10':633,649 '15':106 '2':129,170,310,381,417,494,538,579,692,764,812,816,820,848 '3':133,176,317,385,420,500,544,583,638,696,772,850 '4':137,182,322,390,423,505,550,589,700,780 '5':187,341,349,393,510,555,595,705 'abbrevi':664 'access':223,581 'acronym':662 'act':71,99,151,211,253,436 'action':522 'actual':825 'add':240,394,706 'algorithm':551 'alway':142 'analog':355,666 'analysi':287,300,477,481,525,537,859,861 'analyz':482,526 'api':442,445 'applic':471 'appropri':441 'architect':252,258 'architectur':119,281 'area':514,519 'arrang':435 'arrange-act-assert':434 'ask':74,979 'assert':437 'assess':177,502 'authent':466 'authentication/authorization':580 'avail':675 'avoid':231 'awesom':15,38,919 'awesome-chatgpt-prompt':14,37,918 'background':887 'base':69,95 'battl':9,32 'battle-test':8,31 'before/after':400 'behavior':845,847,849 'best':23,46,934 'better':135 'big':535 'bodi':459 'bottleneck':546 'boundari':274,424,987 'brainstorm':606,608 'bug':125,164,328 'case':166,419,736 'categori':92,653 'caus':312 'caveat':869 'caveat1':870 'chain':746 'chang':404 'chatgpt':16,39,920 'check':162,576,673 'checklist':873 'clarif':981 'classifi':599 'clean':113 'clear':141,222,238,273,878,954 'clever':148 'code':114,122,149,155,172,241,294,298,321,370,374,412,463,479,528,572,680,683 'codebas':487 'cohes':501,504 'collect':6,29 'comment':395 'communic':836 'communiti':22,45 'complet':822 'complex':218,480,484,490,492,534,540,626 'compon':499,771 'comprehens':5,28,408 'concept':220,344 'condit':422 'confid':866 'consid':203,245,262 'constraint':903 'construct':691 'context':885,939 'control':582 'convent':179,429 'convert':717,719 'correct':320 'cost':278 'cot':749 'coupl':495,498 'craft':875 'creativ':604 'criteria':910,990 'critic':197,508 'critical/high/medium/low':603 'cyclomat':489 'daili':364 'data':584,587,729 'databas':547 'debt':512 'debug':292,295,331 'decis':282 'defin':904 'depend':506,509,596,628,708 'describ':958 'descript':431,621,654 'design':259 'desir':944 'develop':98,104 'disk':549 'document':215,224,443,446 'domain':674 'done':207 'dri':384 'duplic':383 'easi':558 'edg':165,418,735 'effici':279 'eli5':342 'endpoint':449,451 'engag':368 'engin':744 'ensur':877 'environ':970 'environment-specif':969 'equival':690 'error':168,421,462 'etc':594 'evalu':171 'everyday':354 'evoc':658 'exact':307,699,881 'exampl':77,192,235,362,461,797,801,804,808,811,814,818,897,902,942 'experi':109,249 'expert':97,102,216,975 'explain':138,337,343,669 'explan':402,716 'fail':309,316 'fault':268 'featur':607,609,614,631,695 'feel':661 'few-shot':790 'final':781 'find':496,561 'first':380,758 'fix':200,318 'follow':225,297,375,701,856 'format':193,472,718,722,725,733,858,890 'framework':427 'fun':367 'function':389,493,698 'generat':444,632,643,644 'github.com':19,42,923 'github.com/f/awesome-chatgpt-prompts)':18,41,922 'given':898 'good':915 'handl':169,588,693,734 'happi':414 'head':239 'help':244 'highlight':513 'horizont':264 'i/o':545 'idea':634 'identif':305 'identifi':124,183,491,689,768 'idiom':704 'idiomat':731 'impact':563 'impact/effort':640 'implement':625 'improv':88,132,189,872 'includ':233,302,430,450,889,941 'incompat':694 'ineffici':553 'inform':888 'inject':590 'input':574,578,803,805,813,815,824,826,984 'inspir':12,35,79 'issu':128,186,198,531,552,600 'jargon':232,358 'json':857 'key':770 'known':597 'languag':230,703 'latenc':276 'learn':793,927 'learnprompting.org':930 'learnprompting.org/)':929 'let':750 'level':250 'librari':3,26 'life':365 'like':338 'limit':469,906,946 'line':620 'll':760,767,775,783 'logic':779 'low/med/high':627 'm':340,348 'maintain':146,271 'map':507 'markdown':476 'match':955 'mean':465 'meaning':391 'measur':914 'memor':663 'memori':541 'metaphor':665 'method':454 'migrat':679,681,711 'miss':992 'mock':439 'modul':503 'modular':272 'must':199 'name':178,392,433,616,642,645 'necessari':398,707 'need':59,80,515 'network':548 'next':773 'o':536 'object':879 'old':351 'one':619 'one-lin':618 'openapi/swagger':474 'optim':559 'option':650 'organ':175 'output':739,807,809,817,819,827,852,894,916,945,964 'paramet':456 'path':415,457 'pattern':85,136,438,543,554,676,829 'per':388 'perform':131,275,524,530,566 'permiss':985 'persona':828,832 'potenti':127,184 'practic':24,47,234 'pragmat':118 'prais':204 'preserv':697,727 'prevent':323,326 'principl':116,227 'priorit':143,560,841 'prioriti':377 'problem':304,763 'process':333 'product':611 'project/feature':647 'prompt':2,11,17,25,34,40,64,70,76,84,90,91,96,291,478,605,678,743,871,876,921,928,935 'prompt-librari':1 'prompts.chat':925,926 'proposit':624 'protect':585 'provid':280,319,521,615,648,740,886,938 'queri':458 'question':788 'quick':556 'rank':636 'rate':468,517 'ratio':641 'readabl':144,181,379 'reader':247 'readi':61 'ready-to-us':60 'reason':140,671 'rec1':864 'rec2':865 'recommend':134,523,863 'redund':270 'refactor':371,372,516 'refer':901 'relat':361 'reliabl':267 'remov':382 'request':455 'request/response':460 'requir':467,726,908,983 'resourc':917 'respond':844,853 'respons':387 'review':121,150,156,195,565,569,976 'role':68,94,158 'role-bas':67,93 'root':311 'safeti':986 'sampl':741 'scalabl':263 'scale':261 'scenario':416 'scope':957 'secur':185,564,568 'senior':154,256 'sensit':586 'sentenc':360 'sever':602 'short':359 'shot':792 'show':329,399,709 'similar':327 'simpl':229,353 'singl':386 'skill':52,55,949 'skill-prompt-library' 'snippet':242 'softwar':103 'solid':115 'solut':786 'solv':752 'sourc':685,721 'source-sickn33' 'space':539 'special':111 'specif':83,191,290,937,971 'specifi':891 'sql':592 'step':334,336,712,714,754,756 'stop':977 'structur':173,236,851,896 'style':837,839 'substitut':967 'success':909,989 'suggest':130,188,201 'system':251,257 'target':687,702,724,732 'task':82,289,800,953 'task-specif':81,288 'technic':209,214,219,357,511 'techniqu':745 'templat':65 'test':10,33,406,409,428,432,973 'thought':332,748 'throughput':277 'tight':497 'time':533 'tip':932 'toler':269 'tone':369 'top':637 'topic-agent-skills' 'topic-agentic-skills' 'topic-ai-agent-skills' 'topic-ai-agents' 'topic-ai-coding' 'topic-ai-workflows' 'topic-antigravity' 'topic-antigravity-skills' 'topic-claude-code' 'topic-claude-code-skills' 'topic-codex-cli' 'topic-codex-skills' 'trade':285 'trade-off':284 'trait':834 'transform':217,677 'treat':962 'understand':761 'url':452 'usag':542 'use':50,53,63,228,352,426,730,947 'user':58,622 'valid':575,737,972 'valu':425,623,842 'verif':742 'verifi':784 'vertic':266 'vulner':591,598 'want':66,86,884 'well':208 'win':557 'work':776 'write':405,407 'writer':210 'x':73 'xss':593 'year':107,350","prices":[{"id":"1e79adcc-60ed-4646-9c0d-169ca6994919","listingId":"79c71053-3e2e-4e31-8da1-dd675e9f4895","amountUsd":"0","unit":"free","nativeCurrency":null,"nativeAmount":null,"chain":null,"payTo":null,"paymentMethod":"skill-free","isPrimary":true,"details":{"org":"sickn33","category":"antigravity-awesome-skills","install_from":"skills.sh"},"createdAt":"2026-04-18T21:42:58.584Z"}],"sources":[{"listingId":"79c71053-3e2e-4e31-8da1-dd675e9f4895","source":"github","sourceId":"sickn33/antigravity-awesome-skills/prompt-library","sourceUrl":"https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/prompt-library","isPrimary":false,"firstSeenAt":"2026-04-18T21:42:58.584Z","lastSeenAt":"2026-04-23T00:51:26.496Z"}],"details":{"listingId":"79c71053-3e2e-4e31-8da1-dd675e9f4895","quickStartSnippet":null,"exampleRequest":null,"exampleResponse":null,"schema":null,"openapiUrl":null,"agentsTxtUrl":null,"citations":[],"useCases":[],"bestFor":[],"notFor":[],"kindDetails":{"org":"sickn33","slug":"prompt-library","github":{"repo":"sickn33/antigravity-awesome-skills","stars":34616,"topics":["agent-skills","agentic-skills","ai-agent-skills","ai-agents","ai-coding","ai-workflows","antigravity","antigravity-skills","claude-code","claude-code-skills","codex-cli","codex-skills","cursor","cursor-skills","developer-tools","gemini-cli","gemini-skills","kiro","mcp","skill-library"],"license":"mit","html_url":"https://github.com/sickn33/antigravity-awesome-skills","pushed_at":"2026-04-22T06:40:00Z","description":"Installable GitHub library of 1,400+ agentic skills for Claude Code, Cursor, Codex CLI, Gemini CLI, Antigravity, and more. Includes installer CLI, bundles, workflows, and official/community skill collections.","skill_md_sha":"6bd89613c209c7d495a3db19a4b89b8e6f06d2d2","skill_md_path":"skills/prompt-library/SKILL.md","default_branch":"main","skill_tree_url":"https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/prompt-library"},"layout":"multi","source":"github","category":"antigravity-awesome-skills","frontmatter":{"name":"prompt-library","description":"A comprehensive collection of battle-tested prompts inspired by [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) and community best practices."},"skills_sh_url":"https://skills.sh/sickn33/antigravity-awesome-skills/prompt-library"},"updatedAt":"2026-04-23T00:51:26.496Z"}}